Abstract
Among the huge number of functionalities that are required for autonomous navigation, the most important are localization, mapping, and path planning. In this article, investigation of the path planning problem of unmanned ground vehicle is based on optimal control theory and simultaneous localization and mapping. A new approach of optimal simultaneous localization, mapping, and path planning is proposed. Our approach is mainly affected by vehicle’s kinematics and environment constraints. Simultaneous localization, mapping, and path planning algorithm requires two main stages. First, the simultaneous localization and mapping algorithm depends on the robust smooth variable structure filter estimate accurate positions of the unmanned ground vehicle. Then, an optimal path is planned using the aforementioned positions. The aim of the simultaneous localization, mapping, and path planning algorithm is to find an optimal path planning using the Shooting and Bellman methods which minimizes the final time of the unmanned ground vehicle path tracking. The simultaneous localization, mapping, and path planning algorithm has been approved in simulation, experiments, and including real data employing the mobile robot Pioneer [Formula: see text]. The obtained results using smooth variable structure filter–simultaneous localization and mapping positions and the Bellman approach show path generation improvements in terms of accuracy, smoothness, and continuity compared to extended Kalman filter–simultaneous localization and mapping positions.
Highlights
In this article, an optimal path planning problem for unmanned vehicle navigation is investigated
We propose in this article a new approach for simultaneous localization, mapping, and
In section ‘‘EKF-simultaneous localization and mapping (SLAM) algorithm,’’ the EKF-SLAM algorithm is detailed and compared with the proposed smooth variable structure filter (SVSF)-SLAM algorithm. The implementation of this latter is presented in section ‘‘SVSF-SLAM algorithm.’’ In section ‘‘Optimal control,’’ we describe path planning with optimal control
Summary
An optimal path planning problem for unmanned vehicle navigation is investigated. This topic is once in a lifetime of diverse categories of control theory; it is one of serious researches. Optimal path planning requires accurate and robust UGV localization. This system contains two important parts, accurate localization and optimal path planning
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